Few-Shot Learning
Performing a task from just a handful of examples.
Few-shot learning gives a model a small number of demonstrations (in the prompt, for LLMs) and expects it to generalize. Zero-shot uses none; few-shot uses a few. It is a hallmark capability of large language models.